Abstract
Phase modulation induced by target micromotions introduces sidebands in the radar spectral signature returns. Time-frequency distributions facilitate the representation of such modulations in a micro-Doppler signature that is useful in the characterization and classification of targets. Reliable micro-Doppler signature classification requires the use of robust features that are capable of uniquely describing the micromotion. Moreover, future applications of micro-Doppler classification will require meaningful representation of the observed target by using a limited set of values. In this paper, the application of the pseudo-Zernike moments for micro-Doppler classification is introduced. Specifically, the proposed algorithm consists of the extraction of the pseudo-Zernike moments from the cadence velocity diagram (CVD). The use of pseudo-Zernike moments allows invariant features to be obtained that are able to discriminate the content of two-dimensional matrices with a small number of coefficients. The analysis has been conducted both on simulated and on real radar data, demonstrating the effectiveness of the proposed approach for classification purposes.
Highlights
Moving targets illuminated by a radar system introduce frequency modulations caused by the time-varying delay that occurs between the target and the sensor
The target may contain parts that have additional movements with respect to the target main motion. These movements can contribute with frequency modulations around the main Doppler shift and they are commonly referred to as micro-Doppler modulations
It is important to underline that, in the open literature, an unambiguous definition of micro-Doppler effect is not present; within this paper we prefer to associate to the term micro-Doppler all the frequency modulations due to small displacement, rotation, or vibration of secondary parts of the object
Summary
Moving targets illuminated by a radar system introduce frequency modulations caused by the time-varying delay that occurs between the target and the sensor. We present a novel micro-Doppler signature extraction method that is based on the use of pseudo-Zernike moments [16]. The pseudo-Zernike moments were selected as features to discriminate different micro-Doppler signatures, in the novel approach described in this paper. The use of the pseudo-Zernike moments allows the introduction of important characteristics in the representation of a micro-Doppler signature, in order to fit different requirements. The scale invariance can be exploited to use a database acquired at a carrier frequency in an automatic target recognition (ATR) working with a slightly different one Another advantage of the scale invariance for this specific problem is the capability of mitigating physical differences between targets of the same class (e.g. two people walking, a tall and a short one that would introduce different micro-Doppler shift that might lead to wrong classification).
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